“…Therefore, active adaption is a more challenging matter of current research for civil-engineering structures. Active control of civilengineering structures is a rising research trend, which was first introduced by Yao (1972). There are two concepts that are related to active structural control: first, active structures (AS) are structures consisting of both passive (static) members and active (dynamic) members (Soong and Manolis, 1987); second, adaptive structures are structures that can change their geometric configuration and physical properties to meet requirements in response to external stimulation (Miura and Furuya, 1988;Wada, 1990).…”
Section: Introductionmentioning
confidence: 99%
“…Although most studies of structural control focus on enhancing safety during vibration caused by earthquakes or high winds, maintaining serviceability is another important goal in this field (Zuk, 1968;Yao, 1972). In practical applications, there is often considerable uncertainty about in-service loading or conditions, which can significantly influence the serviceability of some flexible structures.…”
Abstract:One of the main problems in controlling the shape of active structures (AS) is to determine the actuations that drive the structure from the current state to the target state. Model-based methods such as stochastic search require a known type of load and relatively long computational time, which limits the practical use of AS in civil engineering. Moreover, additive errors may be produced because of the discrepancy between analytic models and real structures. To overcome these limitations, this paper presents a compound system called WAS, which combines AS with a wireless sensor and actuator network (WSAN). A bio-inspired control framework imitating the activity of the nervous systems of animals is proposed for WAS. A typical example is tested for verification. In the example, a triangular tensegrity prism that aims to maintain its original height is integrated with a WSAN that consists of a central controller, three actuators, and three sensors. The result demonstrates the feasibility of the proposed concept and control framework in cases of unknown loads that include different types, distributions, magnitudes, and directions. The proposed control framework can also act as a supplementary means to improve the efficiency and accuracy of control frameworks based on a common stochastic search.
“…Therefore, active adaption is a more challenging matter of current research for civil-engineering structures. Active control of civilengineering structures is a rising research trend, which was first introduced by Yao (1972). There are two concepts that are related to active structural control: first, active structures (AS) are structures consisting of both passive (static) members and active (dynamic) members (Soong and Manolis, 1987); second, adaptive structures are structures that can change their geometric configuration and physical properties to meet requirements in response to external stimulation (Miura and Furuya, 1988;Wada, 1990).…”
Section: Introductionmentioning
confidence: 99%
“…Although most studies of structural control focus on enhancing safety during vibration caused by earthquakes or high winds, maintaining serviceability is another important goal in this field (Zuk, 1968;Yao, 1972). In practical applications, there is often considerable uncertainty about in-service loading or conditions, which can significantly influence the serviceability of some flexible structures.…”
Abstract:One of the main problems in controlling the shape of active structures (AS) is to determine the actuations that drive the structure from the current state to the target state. Model-based methods such as stochastic search require a known type of load and relatively long computational time, which limits the practical use of AS in civil engineering. Moreover, additive errors may be produced because of the discrepancy between analytic models and real structures. To overcome these limitations, this paper presents a compound system called WAS, which combines AS with a wireless sensor and actuator network (WSAN). A bio-inspired control framework imitating the activity of the nervous systems of animals is proposed for WAS. A typical example is tested for verification. In the example, a triangular tensegrity prism that aims to maintain its original height is integrated with a WSAN that consists of a central controller, three actuators, and three sensors. The result demonstrates the feasibility of the proposed concept and control framework in cases of unknown loads that include different types, distributions, magnitudes, and directions. The proposed control framework can also act as a supplementary means to improve the efficiency and accuracy of control frameworks based on a common stochastic search.
“…An overview of kinetic architecture can be found in (Fox and Kemp, 2009). Although kinetic architecture has been focusing on adaptive structures mostly for movable and shape/space-changing applications, structural engineering has been identifying them as a potential solution to safety and serviceability design problems (Yao, 1972;Housner et al, 1997). The origin of adaptive structures in structural engineering can be attributed to Yao (1972) who introduced the concept of structural control as an alternative approach to safety problems.…”
Section: Introductionmentioning
confidence: 99%
“…Although kinetic architecture has been focusing on adaptive structures mostly for movable and shape/space-changing applications, structural engineering has been identifying them as a potential solution to safety and serviceability design problems (Yao, 1972;Housner et al, 1997). The origin of adaptive structures in structural engineering can be attributed to Yao (1972) who introduced the concept of structural control as an alternative approach to safety problems. However, nowadays adaptive structures are employed for applications that span beyond safety, as structural control against long return-period phenomena is not widely accepted due to cost and reliability issues (Housner et al, 1997;Domer and Smith, 2005).…”
Structural engineering, prompted by advances in mechanics and computing as well as design principles such as sustainability and resilience, is evolving towards adaptive structures. Adaptive structures are structures that use active components to change shape and properties in response to their environment and/or to their users' desires. Form-found structures, such as tensegrity and shell structures, can be designed to accommodate such changes within their structural behavior. Dialectic form finding is an extension of the traditional form-finding process integrating performance-related constraints and criteria in the search of a geometry in static equilibrium. Two examples of dialectic form-found structurally integrated adaptive structures are presented. The first example is a shape-shifting tensegrity-inspired structure, while the second example is a shapeshifting shell structure. Both systems are designed to explore elastic deformations for shape changes reducing actuation requirements and highlighting the potential of the proposed method.
“…Control of civil engineering structures was first introduced by Yao [3] as a means of protecting tall buildings against high winds. A modern concept of an active structure was proposed by Soong and Manolis [4], who described an active structure as one consisting of two types of load-resisting members: static (passive) members and dynamic (active) members.…”
Tensegrity structures are spatial, reticulate and lightweight systems composed of struts and cables. Stability is provided by a self-stress state between tensioned and compressed elements. Tensegrities have received interest among scientists and engineers in fields such as architecture, civil and aerospace engineering. Flexibility and ease of tuning make these systems attractive for controllable and adaptive structures. However, tensegrities are often prone to difficulties associated with meeting serviceability criteria and with providing adequate damage tolerance when used as civil engineering structures. This paper extends research on active control of tensegrity structures to study self-repair of a tensegrity pedestrian bridge that is damaged. Selfrepair is intended to meet safety and serviceability requirements in case of cable damage in the pedestrian bridge. Intelligent control methodologies that implement stochastic search with active member grouping are proposed. Case studies for several damage scenarios are presented to show the effectiveness of the methodology. Results from simulated damage scenarios show that self-repair can be successfully performed with a minimum number of active members leading to reductions in control complexity.
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